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<div class="title">actionNet.h</div>  </div>
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<a href="actionNet_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * copy of this software and associated documentation files (the &quot;Software&quot;),</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * to deal in the Software without restriction, including without limitation</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * the rights to use, copy, modify, merge, publish, distribute, sublicense,</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * and/or sell copies of the Software, and to permit persons to whom the</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * Software is furnished to do so, subject to the following conditions:</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> * all copies or substantial portions of the Software.</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * DEALINGS IN THE SOFTWARE.</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160; </div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="preprocessor">#ifndef __ACTION_NET_H__</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#define __ACTION_NET_H__</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160; </div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160; </div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tensorNet_8h.html">tensorNet.h</a>&quot;</span></div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160; </div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160; </div>
<div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="group__actionNet.html#gaa414276f3672cd7092f4cb6ba2c60a4a">   34</a></span>&#160;<span class="preprocessor">#define ACTIONNET_DEFAULT_INPUT   &quot;input&quot;</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160; </div>
<div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="group__actionNet.html#ga98ce3a39afbda984f4d161e907b72b68">   40</a></span>&#160;<span class="preprocessor">#define ACTIONNET_DEFAULT_OUTPUT  &quot;output&quot;</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="group__actionNet.html#ga633a30361913dbff313a41aaf5ad37ce">   46</a></span>&#160;<span class="preprocessor">#define ACTIONNET_MODEL_TYPE &quot;action&quot;</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="group__actionNet.html#ga71fa83f9bb669c46ce0cf85f6cdb0879">   52</a></span>&#160;<span class="preprocessor">#define ACTIONNET_USAGE_STRING  &quot;actionNet arguments: \n&quot;                                                       \</span></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="preprocessor">                  &quot;  --network=NETWORK    pre-trained model to load, one of the following:\n&quot;   \</span></div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;<span class="preprocessor">                  &quot;                           * resnet-18 (default)\n&quot;                                          \</span></div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;<span class="preprocessor">                  &quot;                           * resnet-34\n&quot;                                                    \</span></div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="preprocessor">                  &quot;  --model=MODEL        path to custom model to load (.onnx)\n&quot;                       \</span></div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="preprocessor">                  &quot;  --labels=LABELS      path to text file containing the labels for each class\n&quot;                             \</span></div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;<span class="preprocessor">                  &quot;  --input-blob=INPUT   name of the input layer (default is &#39;&quot; ACTIONNET_DEFAULT_INPUT &quot;&#39;)\n&quot;         \</span></div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="preprocessor">                  &quot;  --output-blob=OUTPUT name of the output layer (default is &#39;&quot; ACTIONNET_DEFAULT_OUTPUT &quot;&#39;)\n&quot;       \</span></div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;<span class="preprocessor">                  &quot;  --threshold=CONF     minimum confidence threshold for classification (default is 0.01)\n&quot;  \</span></div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="preprocessor">                  &quot;  --skip-frames=SKIP   how many frames to skip between classifications (default is 1)\n&quot;         \</span></div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;<span class="preprocessor">                  &quot;  --profile            enable layer profiling in TensorRT\n\n&quot;</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160; </div>
<div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="group__actionNet.html">   69</a></span>&#160;<span class="keyword">class </span><a class="code" href="group__actionNet.html#classactionNet">actionNet</a> : <span class="keyword">public</span> <a class="code" href="group__tensorNet.html#classtensorNet">tensorNet</a></div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;{</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__actionNet.html#classactionNet">actionNet</a>* <a class="code" href="group__actionNet.html#a981fd607b193866dd90a3e824539a961">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* network=<span class="stringliteral">&quot;resnet-18&quot;</span>, uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;                                                 <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;                                                 <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        </div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__actionNet.html#classactionNet">actionNet</a>* <a class="code" href="group__actionNet.html#a981fd607b193866dd90a3e824539a961">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* model_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* class_labels, </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;                                                <span class="keyword">const</span> <span class="keywordtype">char</span>* input=<a class="code" href="group__actionNet.html#gaa414276f3672cd7092f4cb6ba2c60a4a">ACTIONNET_DEFAULT_INPUT</a>, </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;                                                <span class="keyword">const</span> <span class="keywordtype">char</span>* output=<a class="code" href="group__actionNet.html#ga98ce3a39afbda984f4d161e907b72b68">ACTIONNET_DEFAULT_OUTPUT</a>, </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                                                uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>,</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;                                                <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__actionNet.html#classactionNet">actionNet</a>* <a class="code" href="group__actionNet.html#a981fd607b193866dd90a3e824539a961">Create</a>( <span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv );</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__actionNet.html#classactionNet">actionNet</a>* <a class="code" href="group__actionNet.html#a981fd607b193866dd90a3e824539a961">Create</a>( <span class="keyword">const</span> <a class="code" href="group__commandLine.html#classcommandLine">commandLine</a>&amp; cmdLine );</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160; </div>
<div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="group__actionNet.html#a4e70dfc16132513fdec7894224ae71e5">  109</a></span>&#160;        <span class="keyword">static</span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__actionNet.html#a4e70dfc16132513fdec7894224ae71e5">Usage</a>()               { <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#ga71fa83f9bb669c46ce0cf85f6cdb0879">ACTIONNET_USAGE_STRING</a>; }</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160; </div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        <span class="keyword">virtual</span> <a class="code" href="group__actionNet.html#a90871793d4922b61bc7ac81d7355d685">~actionNet</a>();</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        </div>
<div class="line"><a name="l00130"></a><span class="lineno"><a class="line" href="group__actionNet.html#a4338f944254f92fe33572ea1cc7a9736">  130</a></span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt; <span class="keywordtype">int</span> <a class="code" href="group__actionNet.html#a4338f944254f92fe33572ea1cc7a9736">Classify</a>( T* image, uint32_t width, uint32_t height, <span class="keywordtype">float</span>* confidence=NULL )          { <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#a4338f944254f92fe33572ea1cc7a9736">Classify</a>((<span class="keywordtype">void</span>*)image, width, height, imageFormatFromType&lt;T&gt;(), confidence); }</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        <span class="keywordtype">int</span> <a class="code" href="group__actionNet.html#a4338f944254f92fe33572ea1cc7a9736">Classify</a>( <span class="keywordtype">void</span>* image, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format, <span class="keywordtype">float</span>* confidence=NULL );</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160; </div>
<div class="line"><a name="l00151"></a><span class="lineno"><a class="line" href="group__actionNet.html#afde433b5b807ef910787f1d999cef79a">  151</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__actionNet.html#afde433b5b807ef910787f1d999cef79a">GetNumClasses</a>()<span class="keyword"> const                                           </span>{ <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#a5174b850866bd1eaf78265c63fc2a9fe">mNumClasses</a>; }</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        </div>
<div class="line"><a name="l00156"></a><span class="lineno"><a class="line" href="group__actionNet.html#abe3946ca2ec6528cde8af9dd90d986ff">  156</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__actionNet.html#abe3946ca2ec6528cde8af9dd90d986ff">GetClassLabel</a>( <span class="keywordtype">int</span> index )<span class="keyword"> const                     </span>{ <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#adcfadd35f1c5bf00e4556d4bb15b7ae4">GetClassDesc</a>(index); }</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        </div>
<div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="group__actionNet.html#adcfadd35f1c5bf00e4556d4bb15b7ae4">  161</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__actionNet.html#adcfadd35f1c5bf00e4556d4bb15b7ae4">GetClassDesc</a>( <span class="keywordtype">int</span> index )<span class="keyword">    const                   </span>{ <span class="keywordflow">return</span> index &gt;= 0 ? <a class="code" href="group__actionNet.html#a2f7c0ff4cdaf4b990790c388b50a74ea">mClassDesc</a>[index].c_str() : <span class="stringliteral">&quot;none&quot;</span>; }</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160; </div>
<div class="line"><a name="l00166"></a><span class="lineno"><a class="line" href="group__actionNet.html#ab1fa2e71897572a2e894cace9078ec36">  166</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__actionNet.html#ab1fa2e71897572a2e894cace9078ec36">GetClassPath</a>()<span class="keyword"> const                                         </span>{ <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#a29b1f93a3060209b526b89307378d0c7">mClassPath</a>.c_str(); }</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160; </div>
<div class="line"><a name="l00171"></a><span class="lineno"><a class="line" href="group__actionNet.html#a8ba975e3e175e751c10e2121d339a4d0">  171</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">float</span> <a class="code" href="group__actionNet.html#a8ba975e3e175e751c10e2121d339a4d0">GetThreshold</a>()<span class="keyword"> const                                                       </span>{ <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#a90efcce12c5ff5dccfbcd45dbd262cdd">mThreshold</a>; }</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;        </div>
<div class="line"><a name="l00178"></a><span class="lineno"><a class="line" href="group__actionNet.html#a9628498f941ed6709c6b2e13bbb79e29">  178</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="group__actionNet.html#a9628498f941ed6709c6b2e13bbb79e29">SetThreshold</a>( <span class="keywordtype">float</span> threshold )                                     { <a class="code" href="group__actionNet.html#a90efcce12c5ff5dccfbcd45dbd262cdd">mThreshold</a> = threshold; }</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        </div>
<div class="line"><a name="l00184"></a><span class="lineno"><a class="line" href="group__actionNet.html#a6516543d67148a4a31efd156579676d4">  184</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__actionNet.html#a6516543d67148a4a31efd156579676d4">GetSkipFrames</a>()<span class="keyword"> const                                           </span>{ <span class="keywordflow">return</span> <a class="code" href="group__actionNet.html#a9d77f144aae3421c668473456326be2e">mSkipFrames</a>; }</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;        </div>
<div class="line"><a name="l00195"></a><span class="lineno"><a class="line" href="group__actionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49">  195</a></span>&#160;        <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="group__actionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49">SetSkipFrames</a>( uint32_t frames )                                    { <a class="code" href="group__actionNet.html#a9d77f144aae3421c668473456326be2e">mSkipFrames</a> = frames; }</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;         </div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        <a class="code" href="group__actionNet.html#a423008d3f4bda6f6a4da403ed76ab0b1">actionNet</a>();</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;        </div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__actionNet.html#ab7938cba42b5a647fa939cef3813b80b">init</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* model_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* class_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* input, <span class="keyword">const</span> <span class="keywordtype">char</span>* output, uint32_t maxBatchSize, <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, <span class="keywordtype">bool</span> allowGPUFallback );</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__actionNet.html#aee90270cb01137ac90e0ead3f3678a90">preProcess</a>( <span class="keywordtype">void</span>* image, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format );</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160; </div>
<div class="line"><a name="l00203"></a><span class="lineno"><a class="line" href="group__actionNet.html#a35c03812e2928fb8b551de9a96ddc243">  203</a></span>&#160;        <span class="keywordtype">float</span>* <a class="code" href="group__actionNet.html#a35c03812e2928fb8b551de9a96ddc243">mInputBuffers</a>[2];</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        </div>
<div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="group__actionNet.html#a5174b850866bd1eaf78265c63fc2a9fe">  205</a></span>&#160;        uint32_t <a class="code" href="group__actionNet.html#a5174b850866bd1eaf78265c63fc2a9fe">mNumClasses</a>;</div>
<div class="line"><a name="l00206"></a><span class="lineno"><a class="line" href="group__actionNet.html#a122332ccd3dc605278035fcbde9904a2">  206</a></span>&#160;        uint32_t <a class="code" href="group__actionNet.html#a122332ccd3dc605278035fcbde9904a2">mNumFrames</a>;    <span class="comment">// number of frames fed into the model</span></div>
<div class="line"><a name="l00207"></a><span class="lineno"><a class="line" href="group__actionNet.html#a9d77f144aae3421c668473456326be2e">  207</a></span>&#160;        uint32_t <a class="code" href="group__actionNet.html#a9d77f144aae3421c668473456326be2e">mSkipFrames</a>;   <span class="comment">// number of frames to skip when processing</span></div>
<div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="group__actionNet.html#ab613fe5ebe9cb20de9a09acee631bb96">  208</a></span>&#160;        uint32_t <a class="code" href="group__actionNet.html#ab613fe5ebe9cb20de9a09acee631bb96">mFramesSkipped</a>;        <span class="comment">// frame skip counter</span></div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        </div>
<div class="line"><a name="l00210"></a><span class="lineno"><a class="line" href="group__actionNet.html#a023316e6c0b31d1ccaa8d1a22c8df88b">  210</a></span>&#160;        uint32_t <a class="code" href="group__actionNet.html#a023316e6c0b31d1ccaa8d1a22c8df88b">mCurrentInputBuffer</a>;</div>
<div class="line"><a name="l00211"></a><span class="lineno"><a class="line" href="group__actionNet.html#a6b671ec5d2faa557f000692b9447ae0b">  211</a></span>&#160;        uint32_t <a class="code" href="group__actionNet.html#a6b671ec5d2faa557f000692b9447ae0b">mCurrentFrameIndex</a>;</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00213"></a><span class="lineno"><a class="line" href="group__actionNet.html#a90efcce12c5ff5dccfbcd45dbd262cdd">  213</a></span>&#160;        <span class="keywordtype">float</span> <a class="code" href="group__actionNet.html#a90efcce12c5ff5dccfbcd45dbd262cdd">mThreshold</a>;</div>
<div class="line"><a name="l00214"></a><span class="lineno"><a class="line" href="group__actionNet.html#ae44f92239ad5e5bb4be17c7d9b6ad29e">  214</a></span>&#160;        <span class="keywordtype">float</span> <a class="code" href="group__actionNet.html#ae44f92239ad5e5bb4be17c7d9b6ad29e">mLastConfidence</a>;</div>
<div class="line"><a name="l00215"></a><span class="lineno"><a class="line" href="group__actionNet.html#a14c7f294e6b44bbbf64d0e51d065b667">  215</a></span>&#160;        <span class="keywordtype">int</span>   <a class="code" href="group__actionNet.html#a14c7f294e6b44bbbf64d0e51d065b667">mLastClassification</a>;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;        </div>
<div class="line"><a name="l00217"></a><span class="lineno"><a class="line" href="group__actionNet.html#a2f7c0ff4cdaf4b990790c388b50a74ea">  217</a></span>&#160;        std::vector&lt;std::string&gt; <a class="code" href="group__actionNet.html#a2f7c0ff4cdaf4b990790c388b50a74ea">mClassDesc</a>;</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160; </div>
<div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="group__actionNet.html#a29b1f93a3060209b526b89307378d0c7">  219</a></span>&#160;        std::string <a class="code" href="group__actionNet.html#a29b1f93a3060209b526b89307378d0c7">mClassPath</a>;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;};</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160; </div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160; </div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;<span class="preprocessor">#endif</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="agroup__actionNet_html_abe3946ca2ec6528cde8af9dd90d986ff"><div class="ttname"><a href="group__actionNet.html#abe3946ca2ec6528cde8af9dd90d986ff">actionNet::GetClassLabel</a></div><div class="ttdeci">const char * GetClassLabel(int index) const</div><div class="ttdoc">Retrieve the description of a particular class.</div><div class="ttdef"><b>Definition:</b> actionNet.h:156</div></div>
<div class="ttc" id="agroup__actionNet_html_aee90270cb01137ac90e0ead3f3678a90"><div class="ttname"><a href="group__actionNet.html#aee90270cb01137ac90e0ead3f3678a90">actionNet::preProcess</a></div><div class="ttdeci">bool preProcess(void *image, uint32_t width, uint32_t height, imageFormat format)</div></div>
<div class="ttc" id="agroup__actionNet_html_a6516543d67148a4a31efd156579676d4"><div class="ttname"><a href="group__actionNet.html#a6516543d67148a4a31efd156579676d4">actionNet::GetSkipFrames</a></div><div class="ttdeci">uint32_t GetSkipFrames() const</div><div class="ttdoc">Return the number of frames that are skipped in between classifications.</div><div class="ttdef"><b>Definition:</b> actionNet.h:184</div></div>
<div class="ttc" id="agroup__actionNet_html_a29b1f93a3060209b526b89307378d0c7"><div class="ttname"><a href="group__actionNet.html#a29b1f93a3060209b526b89307378d0c7">actionNet::mClassPath</a></div><div class="ttdeci">std::string mClassPath</div><div class="ttdef"><b>Definition:</b> actionNet.h:219</div></div>
<div class="ttc" id="agroup__actionNet_html_a35c03812e2928fb8b551de9a96ddc243"><div class="ttname"><a href="group__actionNet.html#a35c03812e2928fb8b551de9a96ddc243">actionNet::mInputBuffers</a></div><div class="ttdeci">float * mInputBuffers[2]</div><div class="ttdef"><b>Definition:</b> actionNet.h:203</div></div>
<div class="ttc" id="agroup__actionNet_html_a14c7f294e6b44bbbf64d0e51d065b667"><div class="ttname"><a href="group__actionNet.html#a14c7f294e6b44bbbf64d0e51d065b667">actionNet::mLastClassification</a></div><div class="ttdeci">int mLastClassification</div><div class="ttdef"><b>Definition:</b> actionNet.h:215</div></div>
<div class="ttc" id="agroup__actionNet_html_a8ba975e3e175e751c10e2121d339a4d0"><div class="ttname"><a href="group__actionNet.html#a8ba975e3e175e751c10e2121d339a4d0">actionNet::GetThreshold</a></div><div class="ttdeci">float GetThreshold() const</div><div class="ttdoc">Return the confidence threshold used for classification.</div><div class="ttdef"><b>Definition:</b> actionNet.h:171</div></div>
<div class="ttc" id="agroup__actionNet_html_a023316e6c0b31d1ccaa8d1a22c8df88b"><div class="ttname"><a href="group__actionNet.html#a023316e6c0b31d1ccaa8d1a22c8df88b">actionNet::mCurrentInputBuffer</a></div><div class="ttdeci">uint32_t mCurrentInputBuffer</div><div class="ttdef"><b>Definition:</b> actionNet.h:210</div></div>
<div class="ttc" id="agroup__actionNet_html_gaa414276f3672cd7092f4cb6ba2c60a4a"><div class="ttname"><a href="group__actionNet.html#gaa414276f3672cd7092f4cb6ba2c60a4a">ACTIONNET_DEFAULT_INPUT</a></div><div class="ttdeci">#define ACTIONNET_DEFAULT_INPUT</div><div class="ttdoc">Name of default input blob for actionNet model.</div><div class="ttdef"><b>Definition:</b> actionNet.h:34</div></div>
<div class="ttc" id="agroup__actionNet_html_a6b671ec5d2faa557f000692b9447ae0b"><div class="ttname"><a href="group__actionNet.html#a6b671ec5d2faa557f000692b9447ae0b">actionNet::mCurrentFrameIndex</a></div><div class="ttdeci">uint32_t mCurrentFrameIndex</div><div class="ttdef"><b>Definition:</b> actionNet.h:211</div></div>
<div class="ttc" id="agroup__actionNet_html_a90efcce12c5ff5dccfbcd45dbd262cdd"><div class="ttname"><a href="group__actionNet.html#a90efcce12c5ff5dccfbcd45dbd262cdd">actionNet::mThreshold</a></div><div class="ttdeci">float mThreshold</div><div class="ttdef"><b>Definition:</b> actionNet.h:213</div></div>
<div class="ttc" id="agroup__actionNet_html_classactionNet"><div class="ttname"><a href="group__actionNet.html#classactionNet">actionNet</a></div><div class="ttdoc">Action/activity classification on a sequence of images or video, using TensorRT.</div><div class="ttdef"><b>Definition:</b> actionNet.h:69</div></div>
<div class="ttc" id="agroup__actionNet_html_ae44f92239ad5e5bb4be17c7d9b6ad29e"><div class="ttname"><a href="group__actionNet.html#ae44f92239ad5e5bb4be17c7d9b6ad29e">actionNet::mLastConfidence</a></div><div class="ttdeci">float mLastConfidence</div><div class="ttdef"><b>Definition:</b> actionNet.h:214</div></div>
<div class="ttc" id="agroup__actionNet_html_a9628498f941ed6709c6b2e13bbb79e29"><div class="ttname"><a href="group__actionNet.html#a9628498f941ed6709c6b2e13bbb79e29">actionNet::SetThreshold</a></div><div class="ttdeci">void SetThreshold(float threshold)</div><div class="ttdoc">Set the confidence threshold used for classification.</div><div class="ttdef"><b>Definition:</b> actionNet.h:178</div></div>
<div class="ttc" id="agroup__actionNet_html_ga71fa83f9bb669c46ce0cf85f6cdb0879"><div class="ttname"><a href="group__actionNet.html#ga71fa83f9bb669c46ce0cf85f6cdb0879">ACTIONNET_USAGE_STRING</a></div><div class="ttdeci">#define ACTIONNET_USAGE_STRING</div><div class="ttdoc">Standard command-line options able to be passed to actionNet::Create()</div><div class="ttdef"><b>Definition:</b> actionNet.h:52</div></div>
<div class="ttc" id="agroup__actionNet_html_ga98ce3a39afbda984f4d161e907b72b68"><div class="ttname"><a href="group__actionNet.html#ga98ce3a39afbda984f4d161e907b72b68">ACTIONNET_DEFAULT_OUTPUT</a></div><div class="ttdeci">#define ACTIONNET_DEFAULT_OUTPUT</div><div class="ttdoc">Name of default output confidence values for actionNet model.</div><div class="ttdef"><b>Definition:</b> actionNet.h:40</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></div><div class="ttdeci">@ DEVICE_GPU</div><div class="ttdoc">GPU (if multiple GPUs are present, a specific GPU can be selected with cudaSetDevice()</div><div class="ttdef"><b>Definition:</b> tensorNet.h:131</div></div>
<div class="ttc" id="agroup__actionNet_html_a90871793d4922b61bc7ac81d7355d685"><div class="ttname"><a href="group__actionNet.html#a90871793d4922b61bc7ac81d7355d685">actionNet::~actionNet</a></div><div class="ttdeci">virtual ~actionNet()</div><div class="ttdoc">Destroy.</div></div>
<div class="ttc" id="agroup__actionNet_html_a5174b850866bd1eaf78265c63fc2a9fe"><div class="ttname"><a href="group__actionNet.html#a5174b850866bd1eaf78265c63fc2a9fe">actionNet::mNumClasses</a></div><div class="ttdeci">uint32_t mNumClasses</div><div class="ttdef"><b>Definition:</b> actionNet.h:205</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaa5d3f9981cdbd91516c1474006a80fe4"><div class="ttname"><a href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a></div><div class="ttdeci">deviceType</div><div class="ttdoc">Enumeration for indicating the desired device that the network should run on, if available in hardwar...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:129</div></div>
<div class="ttc" id="agroup__actionNet_html_adcfadd35f1c5bf00e4556d4bb15b7ae4"><div class="ttname"><a href="group__actionNet.html#adcfadd35f1c5bf00e4556d4bb15b7ae4">actionNet::GetClassDesc</a></div><div class="ttdeci">const char * GetClassDesc(int index) const</div><div class="ttdoc">Retrieve the description of a particular class.</div><div class="ttdef"><b>Definition:</b> actionNet.h:161</div></div>
<div class="ttc" id="atensorNet_8h_html"><div class="ttname"><a href="tensorNet_8h.html">tensorNet.h</a></div></div>
<div class="ttc" id="agroup__actionNet_html_a4e70dfc16132513fdec7894224ae71e5"><div class="ttname"><a href="group__actionNet.html#a4e70dfc16132513fdec7894224ae71e5">actionNet::Usage</a></div><div class="ttdeci">static const char * Usage()</div><div class="ttdoc">Usage string for command line arguments to Create()</div><div class="ttdef"><b>Definition:</b> actionNet.h:109</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></div><div class="ttdeci">@ TYPE_FASTEST</div><div class="ttdoc">The fastest detected precision should be use (i.e.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:105</div></div>
<div class="ttc" id="agroup__actionNet_html_a122332ccd3dc605278035fcbde9904a2"><div class="ttname"><a href="group__actionNet.html#a122332ccd3dc605278035fcbde9904a2">actionNet::mNumFrames</a></div><div class="ttdeci">uint32_t mNumFrames</div><div class="ttdef"><b>Definition:</b> actionNet.h:206</div></div>
<div class="ttc" id="agroup__actionNet_html_ab7938cba42b5a647fa939cef3813b80b"><div class="ttname"><a href="group__actionNet.html#ab7938cba42b5a647fa939cef3813b80b">actionNet::init</a></div><div class="ttdeci">bool init(const char *model_path, const char *class_path, const char *input, const char *output, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback)</div></div>
<div class="ttc" id="agroup__actionNet_html_ab1fa2e71897572a2e894cace9078ec36"><div class="ttname"><a href="group__actionNet.html#ab1fa2e71897572a2e894cace9078ec36">actionNet::GetClassPath</a></div><div class="ttdeci">const char * GetClassPath() const</div><div class="ttdoc">Retrieve the path to the file containing the class descriptions.</div><div class="ttdef"><b>Definition:</b> actionNet.h:166</div></div>
<div class="ttc" id="agroup__actionNet_html_a423008d3f4bda6f6a4da403ed76ab0b1"><div class="ttname"><a href="group__actionNet.html#a423008d3f4bda6f6a4da403ed76ab0b1">actionNet::actionNet</a></div><div class="ttdeci">actionNet()</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaac6604fd52c6e5db82877390e0378623"><div class="ttname"><a href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a></div><div class="ttdeci">precisionType</div><div class="ttdoc">Enumeration for indicating the desired precision that the network should run in, if available in hard...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:102</div></div>
<div class="ttc" id="agroup__actionNet_html_a4338f944254f92fe33572ea1cc7a9736"><div class="ttname"><a href="group__actionNet.html#a4338f944254f92fe33572ea1cc7a9736">actionNet::Classify</a></div><div class="ttdeci">int Classify(T *image, uint32_t width, uint32_t height, float *confidence=NULL)</div><div class="ttdoc">Append an image to the sequence and classify the action, returning the index of the top class.</div><div class="ttdef"><b>Definition:</b> actionNet.h:130</div></div>
<div class="ttc" id="agroup__actionNet_html_a981fd607b193866dd90a3e824539a961"><div class="ttname"><a href="group__actionNet.html#a981fd607b193866dd90a3e824539a961">actionNet::Create</a></div><div class="ttdeci">static actionNet * Create(const char *network=&quot;resnet-18&quot;, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)</div><div class="ttdoc">Load a pre-trained model, either &quot;resnet-18&quot; or &quot;resnet-34&quot;.</div></div>
<div class="ttc" id="agroup__actionNet_html_ab613fe5ebe9cb20de9a09acee631bb96"><div class="ttname"><a href="group__actionNet.html#ab613fe5ebe9cb20de9a09acee631bb96">actionNet::mFramesSkipped</a></div><div class="ttdeci">uint32_t mFramesSkipped</div><div class="ttdef"><b>Definition:</b> actionNet.h:208</div></div>
<div class="ttc" id="agroup__tensorNet_html_classtensorNet"><div class="ttname"><a href="group__tensorNet.html#classtensorNet">tensorNet</a></div><div class="ttdoc">Abstract class for loading a tensor network with TensorRT.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:218</div></div>
<div class="ttc" id="agroup__actionNet_html_a2f7c0ff4cdaf4b990790c388b50a74ea"><div class="ttname"><a href="group__actionNet.html#a2f7c0ff4cdaf4b990790c388b50a74ea">actionNet::mClassDesc</a></div><div class="ttdeci">std::vector&lt; std::string &gt; mClassDesc</div><div class="ttdef"><b>Definition:</b> actionNet.h:217</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga5a46a965749d6118e01307fd4d4865c9"><div class="ttname"><a href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></div><div class="ttdeci">#define DEFAULT_MAX_BATCH_SIZE</div><div class="ttdoc">Default maximum batch size.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:88</div></div>
<div class="ttc" id="agroup__actionNet_html_afde433b5b807ef910787f1d999cef79a"><div class="ttname"><a href="group__actionNet.html#afde433b5b807ef910787f1d999cef79a">actionNet::GetNumClasses</a></div><div class="ttdeci">uint32_t GetNumClasses() const</div><div class="ttdoc">Retrieve the number of image recognition classes.</div><div class="ttdef"><b>Definition:</b> actionNet.h:151</div></div>
<div class="ttc" id="agroup__commandLine_html_classcommandLine"><div class="ttname"><a href="group__commandLine.html#classcommandLine">commandLine</a></div><div class="ttdoc">Command line parser for extracting flags, values, and strings.</div><div class="ttdef"><b>Definition:</b> commandLine.h:35</div></div>
<div class="ttc" id="agroup__actionNet_html_a0d1b5c7a23698972dc4d1646e2a23d49"><div class="ttname"><a href="group__actionNet.html#a0d1b5c7a23698972dc4d1646e2a23d49">actionNet::SetSkipFrames</a></div><div class="ttdeci">void SetSkipFrames(uint32_t frames)</div><div class="ttdoc">Set the number of frames that are skipped in between classifications.</div><div class="ttdef"><b>Definition:</b> actionNet.h:195</div></div>
<div class="ttc" id="agroup__imageFormat_html_ga931c48e08f361637d093355d64583406"><div class="ttname"><a href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a></div><div class="ttdeci">imageFormat</div><div class="ttdoc">The imageFormat enum is used to identify the pixel format and colorspace of an image.</div><div class="ttdef"><b>Definition:</b> imageFormat.h:49</div></div>
<div class="ttc" id="agroup__actionNet_html_a9d77f144aae3421c668473456326be2e"><div class="ttname"><a href="group__actionNet.html#a9d77f144aae3421c668473456326be2e">actionNet::mSkipFrames</a></div><div class="ttdeci">uint32_t mSkipFrames</div><div class="ttdef"><b>Definition:</b> actionNet.h:207</div></div>
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